Determination of the requirements on plant protection agents

ABSTRACT

The present invention relates to the cultivation of crop plants using plant protection agents. Objects of the present invention are methods, a system and a computer program product for determining the partial-area-specific requirement of a crop plant for plant protection agents.

The present invention relates to the cultivation of crop plants usingplant protection agents. The subject matter of the present invention isa method, a system and a computer program product for determining thepartial-area-specific requirement of a crop plant for plant protectionagents.

Plant protection agents are used throughout the world for protectingplants or plant products from harmful organisms or preventing the actionthereof, destroying unwanted plants or plant parts, inhibiting theunwanted growth of plants or preventing such growth, and/or in anothermanner as nutrients for affecting the physiological processes of plants(e.g. growth regulators).

Plant protection agents may be subject to restrictions on use in somecountries; for example, some plant protection agents can be used only atspecified times, at specified locations, for a specified purpose and/orin a specified amount.

An additional problem in plant protection is the risk of resistanceformation by insects, weeds, and fungi to individual active compounds.

Accordingly, plant protection agents should be used only when requiredand only in the respective amounts necessary.

However, it is difficult to determine the respective requirement forplant protection agents.

The exact dosage of a plant protection agent depends on the biophysicalstate of the vegetation at the exact time of use of the plant protectionagent. In principle, therefore, it would be necessary to determine therequirement immediately before applying a plant protection agent.

In addition, the biophysical state of vegetation is not uniform within afield. Different growth stages can be present that required an adjusteddosage.

Satellite images can provide information on the biophysical state of afield; using such images, moreover, inhomogeneities in a field can berecognized (cf. for example M. S. Moran et al.: Opportunities andLimitations for Image-Based Remote Sensing in Precision Crop Management,Remote Sensing of Environment (1997) 61: 319-346).

However, daily updated information on satellite images is ordinarily notavailable; on the one hand, satellite images are not taken daily in manyareas, and on the other, clouds can for example make the production ofusable remote sensing data difficult or even impossible.

Plant growth models provide the possibility of calculating thebiophysical state of vegetation at future times. For example, WO2016/090212 discloses a method for cultivating plants in which thehistorical data for a field (e.g. weather data) are first used in orderto prepare an initial management plan for the field. The management planis based on a plant growth model and indicates when the crop plantsshould be planted, when measures such as fertilization or wateringshould be carried out, and when the harvest should take place. In asecond step, crop plants are cultivated according to the initialmanagement plan. In a third step, the initial management plans areupdated based on past and predicted weather data, and the initialmanagement plan is replaced with the updated management plan.

US 2016/0171680A1 discloses a method for estimating crop yields.Satellite images of a field are used in order to correlate features inthe satellite images with plant properties and thus to produce astatistical model. For example, it is proposed to correlate the weighteddifference vegetation index (WDVI) with the leaf area index (LAI). Thestatistical model is preferably based on a multivariable linearregression. Environmental conditions are included in the model. Forexample, it is proposed to produce multiple statistical models in orderto cover a broad range of environmental conditions (soil, climate).Based on the model, predictions can then be made, e.g. harvest yieldscan be estimated.

However, the drawback of such plant protection models is that they donot take into account local inhomogeneities within a field.

This gives rise to the technical object of providing a method and asystem for determining the current, partial-area-specific requirement ofa crop plant for plant protection agents.

According to the invention, this object is achieved by means of thesubject matter of independent claims 1, 2, 9 and 11. Preferredembodiments are found in the dependent claims and in the presentdescription.

A first subject matter of the present invention is thus a method fordetermining the amount required by crop plants in a field of one or aplurality of plant protection agents, comprising the following steps:

-   -   (A) detecting inhomogeneities in the field, wherein the        inhomogeneities indicate different existing and/or future growth        stages of the crop plants in the field,    -   (B) segmenting the field into partial areas based on the        inhomogeneities detected in step (A),    -   (C) provision of a plant growth model for the crop plants        cultivated in the field,    -   (D) using the plant growth model on each partial area, wherein        the temporal growth behavior of the crop plant is simulated for        each partial area,    -   (E) determining a requirement of at least a portion of the crop        plants cultivated in the field for treatment with one or a        plurality of plant protection agents, and    -   (F) calculating the partial-area-specific required amount of one        or a plurality of plant protection agents based on the        simulation of growth behavior in step (D) and the requirement        determined in step (E).

A further subject matter of the present invention is a method fortreating crop plants in a field with one or a plurality of plantprotection agents, comprising the following steps:

-   -   (A) detecting inhomogeneities in the field, wherein the        inhomogeneities indicate different existing and/or future growth        stages of the crop plants in the field,    -   (B) segmenting the field into partial areas based on the        inhomogeneities detected in step (A),    -   (C) provision of a plant growth model for the crop plants        cultivated in the field,    -   (D) using the plant growth model on each partial area, wherein        the temporal growth behavior of the crop plant is simulated for        each partial area,    -   (E) determining a requirement of at least a portion of the crop        plants cultivated in the field for treatment with one or a        plurality of plant protection agents,    -   (F) calculating the partial-area-specific required amount of one        or a plurality of plant protection agents based on the        simulation of growth behavior of step (D) and based on the        requirement determined in step (E),    -   (G) preparing a partial-area-specific application map, wherein        the application map is a digital representation of the field        that indicates for individual partial areas of the field the        respective amount(s) of (the) plant protection agent(s) to be        applied, and    -   (H) applying one or a plurality of plant protection agents using        the partial-area-specific application map.

A further subject matter of the present invention is a system comprising

-   -   (a) a digital representation of a field in which crop plants are        cultivated, wherein inhomogeneities are recorded in the digital        representation, wherein the inhomogeneities provide information        on different existing and/or future growth stages of the crop        plants in the field,    -   (b) means for segmenting the digital representation into partial        areas based on the inhomogeneities,    -   (c) a plant growth model for the crop plants cultivated in the        field,    -   (d) means for using the plant model on each partial area,    -   (e) means for receiving a requirement of at least a portion of        the cultivated crop plants for treatment with one or a plurality        of plant protection agents,    -   (f) means for calculating the required amount of one or a        plurality of plant protection agents for each partial area based        on the simulations of the growth behavior, and    -   (g) means for producing a partial-area-specific application map,        wherein the application map is a digital representation of the        field that indicates for individual partial areas of the field        the respective amount(s) of (the) plant protection agent(s) to        be applied.

A further subject matter of the present invention is a computer programproduct comprising a data carrier on which a computer program is stored,which can be loaded into the working memory of a computer and causes thecomputer to carry out the following steps:

-   -   (i) reading a digital representation of a field in which crop        plants are cultivated into the working memory of the computer,        wherein the field in the digital representation is subdivided        into partial areas, wherein at least a portion of the partial        areas differ with respect to existing and/or future growth        behavior of the cultivated crop plants,    -   (ii) calculating the growth behavior of the crop plants        cultivated in the field over time for each individual partial        area by means of a plant growth model,    -   (iii) receiving a requirement of at least a portion of the        cultivated crop plants for treatment with one or a plurality of        plant protection agents,    -   (iv) calculating the required amount of the one or plurality of        plant protection agent(s) for each partial area based on the        calculated growth stage for the respective partial area of the        crop plants cultivated there, and    -   (v) outputting the plant protection agent requirement for each        partial area to a user.

The invention is described in further detail below withoutdistinguishing among the subject matter of the invention (method,system, computer program product). Rather, the following explanationsapply analogously to all subject matter of the invention regardless ofthe context in which they occur (method, system, computer programproduct).

When the “method according to the invention” is mentioned below, this isto be understood as referring both to the method for treating cropplants with one or a plurality of plant protection agents and to themethod for determining the amount required by crop plants of one or aplurality of plant protection agents.

The core of the present invention lies in determining apartial-area-specific amount of one or a plurality of plant protectionagents required by crop plants that are or are to be cultivated in afield.

The term “crop plant” is understood to refer to a plant that iscultivated by human intervention in a targeted manner as a useful orornamental plant.

The term “field” is understood to refer to a spatially delimitable areaof the Earth's surface that is agriculturally used in that crop plantsare cultivated, provided with nutrients and harvested in such a field.

The term “plant protection agents” is understood to refer to an agentthat is used for protecting plants or plant products from harmfulorganisms or preventing the action thereof, destroying unwanted plantsor plant parts, inhibiting the unwanted growth of plants or preventingsuch growth, and/or in another manner as nutrients for affecting thephysiological processes of plants (e.g. growth regulators).

Examples of plant protection agents are herbicides, fungicides andpesticides (such as insecticides).

Growth regulators are used for example for increasing the stability ofgrain by shortening the stem length (stem shorteners, or more preciselyinternode shorteners), improving the rooting of cuttings, reducing plantheight by compression in horticulture or preventing the germination ofpotatoes. They are ordinarily phytohormones or synthetic analogsthereof.

A plant protection agent ordinarily contains an active compound or aplurality of active compounds. The term “active compounds” refers tosubstances that have a specific action and induce a specific reaction inan organism. Ordinarily, a plant protection agent contains a carriersubstance for diluting the one or plurality of active compounds. Inaddition, additives such as preservatives, buffers, dyes and the likeare conceivable. A plant protection agent can be in solid, liquid orgaseous form.

In a first step of the method according to the invention,inhomogeneities in the field in which the crop plants are cultivated areidentified.

The inhomogeneities provide information on differences in the field inwhich the crop plants are cultivated. The inhomogeneities detected canbe an expression of existing differences in the growth behavior of thecrop plants; however, it is also conceivable that the inhomogeneitiesdetected will lead to different growth stages. Mixed forms are alsoconceivable.

The term inhomogeneity preferably refers to existing differences in thegrowth stages of individual plants within the field. Such differencesoccur in every field, as the local environment is different at differentpoints in a field. For example, plants in the edge area of a field areoften exposed to more wind that plants within the field. There are alsovariations in the soil or differences with respect to sunlight exposureof plants on a slope and on level ground.

Accordingly, what is important in determining inhomogeneities is toobtain a picture of the different growth stages of the cultivated plantthat are present or expected respectively in order to allow thesedifferences to be taken into account and to determine the respectiverequired amount of plant protection agents for the different growthstages.

Here, the term “growth stage” is to be understood in the broad sense.The term growth stage can refer to the development stage of individualplants; but it can also refer to the amount of biomass and/or the sizeof the leaf area and/or the amount of fruits and/or the number of shootspresent that a plant has formed at a defined point in time. On the onehand, there are crop plants that are not susceptible to a harmfulorganism until they have reached specified development stages. Thismeans that treatment of the plant with a plant protection agent may notbe effective until the plant has reached the corresponding developmentstage. On the other hand, it is conceivable that a plant with morebiomass and/or a larger leaf area will require a larger amount of plantprotection agents than a plant with less biomass and/or a smaller leafarea. According to the invention, the required amount of plantprotection agents is to be adapted to the development stage of the cropplants and/or the amount of biomass present and/or an the size of theleaf area present and/or the amount of fruits present, etc.

It is therefore characteristic of a growth stage of a crop plant that aspecified type of plant protection agent, a specified amount of plantprotection agent, a specified concentration and/or a specified dosingschedule should be used in order to achieve an optimum effect, whileanother optimum parameter is to be selected for another growth stage.

A possibility for determining inhomogeneities lies in the use of remotesensing data.

“Remote sensing data” are digital data obtained remotely, for example bysatellites, from the Earth's surface. The use of aircraft (unmanned(drones) or manned) to record remote sensing data is also conceivable.

By means of corresponding remote sensors, digital images of areas of theEarth's surface are produced from which information on the vegetationand/or the environmental conditions prevailing in said areas can beobtained (cf. for example M. S. Moran et al.: Opportunities andLimitations for Image-Based Remote Sensing in Precision Crop Management,Remote Sensing of Environment (1997) 61: 319-346).

The data from these sensors are obtained via interfaces provided by thevendor and can comprise optical and electromagnetic (e.g. syntheticaperture radar, SAR) data sets of various processing stages.

In a preferred embodiment, inhomogeneities in the field underobservation are detected from remote sensing data.

A possibility lies for example in calculating a vegetation index fromthe remote sensing data. A known vegetation index is for example thenormalized difference vegetation index (NDVI, also known as thenormalized density vegetation index). The NDVI is calculated from thereflectance values in the near infrared region and the red visibleregion of the light spectrum. The index is based on the fact thathealthy vegetation reflects a relatively small amount of radiation inthe red region of the visible spectrum (wavelength of approximately 600to 700 nm) and a relatively large amount of radiation in the adjacentnear infrared region (wavelength of approximately 700 to 1300 nm). Thesedifferences in reflectance behavior are attributable to differentdevelopment states of the vegetation. Accordingly, the further thegrowth of a cultivated crop plant has progressed, the higher the indexis.

An NDVI can be calculated for each pixel of a digital image of a field(for example a satellite image of the field).

As a further possible vegetation index, the weighted differencevegetation index (WDVI) can also be determined from the remote sensingdata, as proposed in US 2016/0171680 A1, with which the leaf area index(LAI) can be correlated.

A leaf area index can be calculated for each pixel of a digital image ofa field (for example a satellite image of the field).

Instead of or as a complement to remote sensing data, information onexisting and/or expected inhomogeneities can also be obtained by meansof sensors in the field. For example, the use of a so-called N sensor,which can also be used to determine an NDVI, is also conceivable.

A parameter that indicates the inhomogeneities with respect to anexisting and/or future growth stage of the cultivated crop plant in adigital representation of the field is also referred to in the followingas a growth parameter. An example of such a growth parameter is an NDVIor LAI. However, a growth parameter can also be the amount of nutrientsin the soil, the availability of water or the soil temperature. Allparameters that have an effect on the growth and/or development of aplant can be used as growth parameters.

Possible growth parameters are described in the following publications:M. D. Steven and J. A. Clark (1990): Applications of Remote Sensing inAgriculture. University Press, Cambridge/UK,http://www.sciencedirect.com/science/book/9780408047678; A. Bannari, D.Morin, F. Bonn and A. R. Huete (2009): A review of vegetation indices.In: Remote Sensing Reviews, Vol. 13, Issue 1-2, pp. 95-120,http://www.tandfonline.com/doi/abs/10.1080/02757259509532298; A. A.Gitelson (2004): Wide dynamic range vegetation index for remote sensingquantification of biophysical characteristics of vegetation. In: Journalof Plant Physiology, Vol. 161, Issue 2, pp. 165-173, A. Viña, A. A.Gitelson, A. L. Nguy-Robertson and Y. Peng (2011): Comparison ofdifferent vegetation indices for the remote assessment of green leafarea index of crops. In: Remote Sensing of Environment, Vol. 115, pp.3468-3478, https://msu.edu/˜vina/2011_RSE_GLAI.pdf.

In a further step (step (B) of the method according to the invention),segmentation of the field is carried out. This means that a virtualrepresentation of the field is subdivided into partial areas (segments).There is thus no physical intervention in the actual field. Even whenthe term “segmentation of the field” is used herein for simplificationpurposes, this is always to be understood as referring to segmentationof a virtual representation of the field into partial areas. The virtualrepresentation of the field constitutes data that can be processed by acomputer and can be represented using a computer in such a way that auser of the computer will recognize in the representation thecorresponding real field.

Segmentation is ordinarily carried out based on one or a plurality ofgrowth parameters. There are various possibilities for segmentation.

For example, it is conceivable to carry out segmentation based on thespatial resolution of the method for determining the inhomogeneities.This will be explained using an example. Let us assume that there is adigital satellite image of a field for which a growth parameter (e.g. aleaf area index (LAI)) can be determined for each pixel of the digitalimage of the field. The satellite image has a specified spatialresolution; for example, 1 pixel of the satellite image corresponds toan area of 10·10 m² of the imaged field. It is conceivable that apartial area can be assigned to each individual pixel. A partial areathus corresponds to an area of 10·10 m² on the field.

In an embodiment of the present invention, a digital representation of afield is subdivided into individual partial areas, wherein eachindividual pixel of the digital representation represents an individualpartial area.

With increasingly high spatial resolution of the digital representationof the field, the differences between adjacent pixels, e.g. with respectto the leaf area index, become smaller and smaller. It is conceivablethat numerous adjacent pixels indicate the same leaf area. Therefore, itis increasingly appropriate with increasing spatial resolution tocombine adjacent partial areas having the same value for a growthparameter into a partial area.

In a further embodiment of the present invention, therefore, adjacentpixels having the same value for a growth parameter are combined into apartial area.

It is also conceivable to combine adjacent pixels into a partial area ifthey no longer deviate from one another as a predetermined absolute orrelative value.

Further methods of segmentation are conceivable. Segmentation isordinarily carried out in such a manner that partial areas with similarproperties are created. Segmentation takes place using one or aplurality of parameters that represent one or a plurality of propertiesof the field and/or the crop plants cultivated in the field and/or theenvironmental conditions prevailing in the field (growth parameters).Segmentation is preferably carried out so as to minimize the differenceswithin a partial area and maximize the differences between the partialareas. Segmentation can be carried out according to known mathematicalmethods such as e.g. the Jenks-Caspall algorithm.

For example, it is conceivable that segmentation is carried out directlyusing the growth stages of the cultivated crop plants observed in thecurrent cultivation period. In such a case, by means of e.g. remotesensing data, differences in the cultivated crop plants with respect tothe respective growth stages present are determined. In this case,segmentation of the field is carried out such that the crop plants inindividual partial areas are in a comparable growth stage, with thedifferences in the growth stages within a partial area preferably beingsmaller than the differences in the growth stages between the partialareas.

However, it is also conceivable that segmentation is carried out basedon inhomogeneities that have an effect on the growth behavior of thecrop plants. For example, it is conceivable that by means of the remotesensors, differences in the soil properties are detected. For example,it is conceivable that different soil types are present in a field. Itis known for the individual soil types that they lead to differentgrowth of the crop plants. In such a case, segmentation is carried outbased on the different soil properties/soil types.

It is also conceivable for remote sensing data from past cultivationperiods to show historical differences in the growth behavior of thecultivated crop plants. Such historical differences can also be used forsegmentation of the field if they are recurrent.

It is also conceivable to use a plurality of the aforementionedinhomogeneities for segmentation.

It is also conceivable to carry out segmentation based on the wheelgauge or the spray width of the agricultural machines ordinarily used inthe field or to take into account the wheel gauge or the spray width indetermining the size of the segments. If the partial areas are smallerthan the wheel gauge or the spray width, the agricultural machine is notcapable of addressing plant protection agents to individual partialareas in a targeted manner. In an embodiment of the present invention,the size of the partial areas is therefore selected such that it is notsmaller than the spray width of the application device.

In a further step (step (C) of the method according to the invention), aplant protection model is prepared for the crop plants cultivated in thefield. Step (C) can be carried out before, after or during steps (A) and(B).

The term “plant growth model” is understood to refer to a mathematicalmodel that describes the growth of a plant depending on intrinsic(genetic) and extrinsic (environmental) factors.

Plant growth models exist for multiple crop plants. The term “provisionof a plant growth model” is to be understood as meaning both that anexisting model is used and that an existing model is adapted ormodified, and also that a new model is drawn up.

An introduction to the preparation of plant growth models can be foundfor example in the books i) “Mathematische Modellbildung and Simulation[Mathematical Modelling and Simulation]” by Marco Günther and KaiVelten, published by Wiley-VCH Verlag in October 2014 (ISBN:978-3-527-41217-4), and ii) “Working with Dynamic Crop Models” by DanielWallach, David Makowski, James W. Jones and Francois Brun., published in2014 by Academic Press (Elsevier), USA.

The plant growth model ordinarily simulates the growth of a populationof crop plants over a defined period of time. It is also conceivable touse a model based on an individual plant that simulates the energy andmaterial flows in the individual organs of the plant. Mixed models arealso usable.

In addition to the genetic features of the plant, the growth of a cropplant is primarily determined by the local weather prevailing during thelifetime of the plant (quantity and spectral distribution of incidentsolar radiation, temperature gradient, amounts of precipitation, wind),the state of the soil, and the nutrient supply.

The cultivation measures carried out in the past and any infestationwith harmful organisms can also affect plant growth and can be takeninto account in the growth model.

The plant growth models are as a rule so-called dynamic process-basedmodels (cf. “Working with Dynamic Crop Models” by Daniel Wallach, DavidMakowski, James W. Jones and Francois Brun., published 2014 by AcademicPress (Elsevier), USA), but can also be entirely or partially rule-basedor statistical or data-supported/empirical. The models are as a ruleso-called point models. Here, the models are ordinarily calibrated suchthat the output reflects the spatial representation of the input. If theinput is collected at a point in space or if interpolation or estimationis carried out for a point in space, it is generally assumed that themodel output is valid for the entire adjacent field. An application ofso-called point models calibrated at field level to further scales,which as a rule are cruder, is known (Hoffmann et al., 2016). Here,application of these so-called point models to multiple points within afield allows partial-area-specific modeling. However, spatialdependencies are neglected in this case, e.g. in the ground waterbalance. On the other hand, there are also systems fortemporally/spatially explicit modeling. These take into account spatialdependencies.

Examples of dynamic, process-based plant growth models are Apsim,Lintul, Epic, Hermes, Monica, STICS, etc. For example, a comparison ofthe models and corresponding literature on the models can be found inthe following publication and the references contained therein: HoffmannH, Zhao G, Asseng S, Bindi M, Biernath C, Constantin J, Coucheney E,Dechow R, Doro L, Eckersten H, Gaiser T, Grosz B, Heinlein F, Kassie BT, Kersebaum K-C, Klein C, Kuhnert M, Lewan E, Moriondo M, Nendel C,Priesack E, Raynal H, Roggero PP, Rötter R P, Siebert S, Specka X, TaoF, Teixeira E, Trombi G, Wallach D, Weihermüller L, Yeluripati J, EwertF. 2016. Impact of spatial soil and climate input data aggregation onregional yield simulations. PLoS ONE 11(4): e0151782.doi:10.1371/journal.pone.0151782.

The following parameters are preferably included in the modeling(input):

-   -   a) weather: daily precipitation sums, solar radiation sums,        daily minimum and maximum air temperature, temperature near the        ground, soil temperature, wind speed, etc.    -   b) soil: soil type, soil texture, soil texture, kind of soil,        field capacity, permanent wilting point, organic carbon, mineral        nitrogen content, bulk density, van Genuchten parameters, etc.    -   c) crop plant: type, species, species-specific parameters such        as e.g. specific leaf area index, temperature sums, maximum root        depth, etc.    -   d) cultivation measures: seeds, sowing date, sowing density,        sowing depth, fertilizer, fertilizer amount, number of        fertilization dates, fertilization date, soil cultivation, crop        residues, crop rotation, distance from field of same crop in the        previous year, watering, etc.

In a following step (step (D) of the method according to the invention),the plant growth model is used to simulate for each partial area thegrowth of the crop plants cultivated in said area. In this case, theinformation from step (A) and/or (B) is included in the plant growthmodel.

For example, if it has been determined from remote sensing data that thecrop plants cultivated in the field are in different growth stages, andif the field has been segmented into partial areas with similar growthstages, the current growth stage in each partial area is included in thegrowth model as a parameter, and the further (future) growth ispredicted.

For example, if it has been determined from remote sensing data that inpast cultivation periods, the crop plants in several partial areasrepeatedly showed more rapid growth than in other partial areas, thefield is segmented based on the observed growth rate, and the growthrate of each partial area is included in the plant growth model forpredicting the growth in the current cultivation period.

For example, if it has been determined from remote sensing data thatinhomogeneities are present under specified environmental conditions(e.g. soil properties, exposure to sunlight, wind or precipitation,temperature gradient, etc.) and if it is known that theseinhomogeneities lead to different growth of the cultivated crop plants,segmentation of the field is carried out based on these environmentalconditions, and the environmental conditions are included as parameters(growth parameters) in the modeling and prediction of the growthbehavior of the crop plants.

The result of step (D) of the method according to the invention is theexpected course over time of the growth of the crop plants for eachpartial area. The course over time can thus be used to predict thegrowth stage of the crop plants in each partial area for any given daywithin the current cultivation period. Step (D) is carried out aftersteps (A), (B) and (C).

In a further step (step (E) of the method according to the invention), arequirement for treatment with one or a plurality of plant protectionagents is determined for at least a portion of the crop plantscultivated in the field. Step (E) can be carried out before, during orafter steps (A), (B), (C) and (D). It is thus conceivable fordetermination of a requirement to be the trigger for one or more ofsteps (A), (B), (C) and (D). However, it is also conceivable for steps(A), (B), (C) and/or (D) to be carried out on a precautionary basis inorder to “be armed” in the event of an acute requirement.

The requirement for treatment of crop plants with one or a plurality ofplant protection agents can for example arise because a pest infestationhas occurred or is imminent. Instead of a “requirement,” one couldtherefore also speak of an “infestation or risk of infestation with aharmful organism.”

The partial-area-specific requirement is preferably determined usingsensors in and/or over the field.

The use of traps that are set up at various locations in the field canalso make an infestation with harmful organisms detectable.

It is also conceivable to use for determination a requirement predictionmodel, e.g. for predicting pest infestations. Such prediction modelshave been extensively described in the prior art and are alsocommercially available. The decision support system proPlant Expert(Newe et al. 2003, Johnen et al. 2010; www.proPlantexpert.com) uses forprediction purposes data on the cultivated crop plant (developmentstage, growth conditions, plant protection measures), the weather(temperature, sunshine duration, wind speed, precipitation) and theknown pests/diseases (economic limit values, pest/disease pressure).Using these data, an infestation risk is estimated and a recommendationon the time of treatment and plant protection agents and an evaluationof past plant protection measures are generated.

The infestation of an adjacent field by a harmful organism, which isreported For example by a farmer, can also indicate a requirement.

Once the requirement has been determined, the plant protection agent tobe used follows from this. If the requirement is attributable to anacute or imminent infestation with weeds, then the plant protectionagent to be used is a herbicide. The type of weeds determines the typeof usable herbicide. If the requirement is attributable to an acute orimminent fungal infestation, then the plant protection agent to be usedis a fungicide. The type of fungus determines the type of usablefungicide. If the requirement is attributable to an acute or imminentinfestation with an animal pest, then the plant protection agent to beused is a pesticide. The type of animal pest determines the type ofusable pesticides.

Once the requirement has been determined, the time window in which theone or plurality of plant protection agents is/are to be applied alsofollows from this requirement. If there is an acute requirement,application should be carried out immediately. If correspondingpredictions indicate that a requirement is imminent in the near future,application can be carried out immediately, or optionally shortly beforean acute infestation.

In a further step (step (F) of the method according to the invention),the information from steps (E) and (D) of the method according to theinvention is merged: there is a requirement for treatment with one or aplurality of specific plant protection agents; the time window in whichapplication is to carried out (application time window) is known; thegrowth stage in which the crop plants will be in the application timewindow is known. The amounts of the plant protection agents to beapplied must now be calculated. This takes place in step (F) of themethod according to the invention.

The amount of the plant protection agent required is determined by therespective growth stage. Different variables and their differencesbetween two time points can be derived from the growth stage, such ase.g. the size of leaf areas, biomass, fruit amount, etc.

In a preferred embodiment, the amount of the plant protection agentsrequired is calculated based on the leaf areas of the crop plantscultivated at the location in question, which are predicted in apartial-area-specific manner.

For example, if the plant protection agent is a pesticide forcontrolling an animal pest (e.g. caterpillars, beetles, etc.) thatattacks the leaves, the larger the leaf area present, the greater theamount of plant protection agent required. Using the plant growth model,the sizes of the leaf areas can be predicted for the individual partialareas. It is also conceivable (depending on the model used) to predictsize distributions of the leaf areas for the individual partial areas.

Based on the predicted sizes of the leaf areas, one can then calculatethe required amounts of plant protection agents needed for example inorder to provide optimum protection of the leaves from predators.Accordingly, there is preferably a positive linear correlation betweenthe size of the leaf areas and the required amount of plant protectionagents.

In another preferred embodiment, the required amount of plant protectionagents is calculated not on the basis of predicted values for leaf areasbut on the basis of predicted biomass. There is therefore preferably apositive linear correlation between biomass and the required amount ofplant protection agents.

In another preferred embodiment, the required amount of plant protectionagents is calculated based on the predicted fruit area or fruit mass.

In another preferred embodiment, the required amount of plant protectionagents is calculated based on the number of shoots present.

Further connections between variables that can be derived from thepredicted plant growth and the required amount of plant protectionagents are conceivable. For example, it is conceivable that the plantprotection agent is not applied until the crop plants reach a defineddevelopment stage (e.g. have flowers or fruits). It is conceivable thatuntil this stage, no plant protection agent is applied, because aspecified pest ordinarily does not occur until this stage, and from thisstage on, a plant protection agent is applied, and the amount thereofthen increases linearly with the biomass, fruit amount, or another plantparameter present. It is further conceivable that a first plantprotection agent is used up to a specified growth stage and a differentsecond plant protection agent is then used from this growth stage on.

In addition to the crop-plant-related parameters (leaf area, biomass,fruit mass, etc.), there are often further parameters that determine theoptimum amount and/or concentration of a plant protection agent. In apreferred embodiment, such parameters are also taken into account incalculating the partial-area-specific required amounts.

For example, it is conceivable that the respective mechanism of actionof a plant protection agent has an effect on the amount and/orconcentration in which the plant protection agent should be applied inorder to achieve an optimum effect. In a preferred embodiment, themechanism of action of the plant protection agent is therefore includedin calculating the required amounts.

It is also conceivable that environmental conditions at the time ofapplication have an effect on the optimum amount of the plant protectionagent to be used. Such environmental conditions can for example be thetemperature, humidity, sunlight, etc. at the time of application.

For example, it is conceivable that a plant protection agent is veryrapidly broken down by direct sunlight. Perhaps application of the plantprotection agent is planned because of a high risk of infestation at atime when direct sunlight is to be expected. Accordingly, a largeramount is required than under overcast conditions in order to compensatefor the portion broken down by direct sunlight. According to thedescribed embodiment, the requirement for plant protection agents isadapted to correspond to the prevailing environmental conditions.

It is also conceivable that the system for application of the plantprotection agent (application device) is subject to certainrestrictions. For example, it is conceivable that the application devicecomprises a spraying device with which a constant flow of a plantprotection agent can only be switched on and off, but with which theamount of the plant protection agent discharged cannot be varied. Inthis case, it would optionally be possible to set the requirement suchthat the discharge takes place in pulses, wherein the time between twopulses and the pulse length can be varied. In such a case, the result ofcalculation of the amount of plant protection agent required would be apulse length and pulse frequency to be adjusted for the respectivepartial area.

Preferably, a digital application map is produced in a further step(step (G)). The digital application map is a digital representation ofthe field. The application map indicates the amounts of one or aplurality of selected plant protection agents to be applied and thepartial areas of the field to which said agent(s) are to be applied, forexample in order to prevent the spread of harmful organisms and/or tocontrol harmful organisms.

In a further step, the plant protection agent is then applied in apartial-area-specific manner according to the application map.

In a preferred embodiment, the digital application map or parts thereofcan be loaded into the working memory of an application device.

An application device is understood to refer to a mechanical device forapplying a plant protection agent to a field. Such an application devicecomprises as a rule at least one container for accommodating at leastone plant protection agent, a spraying device with which the plantprotection agent is dispensed onto the field, and a control device withwhich feeding of the at least one plant protection agent from itscontainer in the direction of the spraying device is controlled.Accordingly, the digital application map is preferably loaded into theworking memory of the control unit. Moreover, the control unit ispreferably connected to a position-determining system that detects theposition of the application device on the field. Preferably, the controldevice initiates the application process when it is recorded on thedigital application map that application is to take place at a locationand when the position-determining system reports that the applicationdevice is at said location.

In another embodiment, a person (the user) loads the digital applicationmap into a mobile computer system, e.g. a mobile telephone (smartphone)equipped with a GPS receiver. While the user moves over the field, themobile computer system indicates to him/her by means of a graphic imageof the field where he/she is located at any given time and at whichlocations he/she is to spray (apply) one or a plurality of pesticides.The user then carries out spraying at the sites where the applicationmap has a corresponding indication.

Preferably, the present invention is combined with a prediction modelfor predicting pest infestations. Using the prediction model, afield-specific infestation risk is estimated, and a recommendation onthe time of treatment and the plant protection agent, as well as anassessment of past plant protection measures, are generated.

The prediction model thus provides all of the important information onthe use of a plant protection agent except for the respective amounts tobe used in a partial-area-specific manner. In contrast, the presentinvention provides the respective amounts to be used in apartial-area-specific manner.

In the above-mentioned preferred embodiment, a prediction of aninfestation risk is thus carried out. If the infestation risk exceeds athreshold value, a user determines according to the invention thepartial-area-specific requirement for the amount of plant protectionagents to be used and carries out a corresponding partial-area-specificapplication of the plant protection agent.

It is also conceivable for one or a plurality of steps of the methodaccording to the invention to be carried out using a computer or by acomputer.

A further subject matter of the present invention is therefore acomputer program product. The computer program product comprises a datacarrier on which a computer program is stored, which can be loaded intothe working memory of a computer. The computer program causes thecomputer to carry out the steps described below.

A first step (step (i)) consists of reading a digital representation ofa field in which crop plants are cultivated into the working memory ofthe computer.

For example, this digital representation can be a satellite image.However, it is also conceivable that a digital representation of a fieldis produced based on a satellite image in that e.g. the outer boundariesof a field are highlighted in the satellite image by means of graphicmarkings. It is conceivable to identify certain properties of the fieldby means of colored marking. It is conceivable, for example, for an NDVIto be determined for each pixel of the digital satellite image and forfalse color representation to be carried out, with the pixels beingcolored a darker green if the corresponding NDVI shows a high value anda lighter green if the corresponding NDVI shows a low value.

It is conceivable for the digital representation of the field to alreadybe subdivided into partial areas when it is loaded into the workingmemory of the computer. For example, it is conceivable for eachindividual pixel of the digital image to represent a partial area. It isalso conceivable for images already segmented into partial areas to beprovided by a (commercial) vendor.

However, it is also conceivable for the partial areas themselves tofirst be produced using the computer. For this purpose, the digitalrepresentation of the field is analyzed and inhomogeneities in the fieldare detected, wherein the inhomogeneities provide information ondifferent existing and/or future growth stages of the crop plants in thefield. After this, segmentation of the digital representation of thefield into partial areas is carried out based on the detectedinhomogeneities as explained in detail above.

In a further step (step (ii)), the growth behavior of the crop plantscultivated in the field over time is calculated for each individualpartial area by means of a plant growth model. Step (ii) can take placebefore, after or during step (i).

In a further step (step (iii)), a requirement for treatment of the cropplants with one or a plurality of plant protection agents is determinedfor at least a portion of the crop plants cultivated in the field. Step(iii) can be carried out before, after or during steps (i) and (ii).

In a further step (step iv), the information from steps (ii) and (iii)is merged. The respective partial-area-specific required amount isdetermined based on information on a requirement and based on theinformation on the respective growth stage of the crop plants within thepartial areas produced. Accordingly, step (iv) is carried out aftersteps (ii) and (iii).

In a further step (step (v)), the calculated partial-area-specificrequired amount is output to a user in the form of a digital applicationmap. Preferably, the user can transfer the digital application map to anapplication device by means of a mobile data storage medium or via awireless communication link (e.g. Bluetooth).

A further subject matter of the present invention is a system comprisingthe following elements:

-   -   (a) a digital representation of a field in which crop plants are        cultivated, wherein inhomogeneities are recorded in the digital        representation, wherein the inhomogeneities provide information        on different existing and/or future growth stages of the crop        plants in the field,    -   (b) means for segmenting the digital representation into partial        areas based on the inhomogeneities,    -   (c) a plant growth model for the crop plants cultivated in the        field,    -   (d) means for using the plant model on each partial area,    -   (e) means for receiving a requirement of at least a portion of        the cultivated crop plants for treatment with one or a plurality        of plant protection agents,    -   (f) means for calculating the required amount of one or a        plurality of plant protection agents for each partial area based        on the simulations of the growth behavior, and    -   (g) means for producing a partial-area-specific application map,        wherein the application map is a digital representation of the        field that indicates for individual partial areas of the field        the respective amount(s) of (the) plant protection agent(s) to        be applied.

Means (b), (d), (e), (f) and (g) are preferably a stationary or mobilecomputer system. It is conceivable for a plurality of computer systemsnetworked to one another to be used; however, it is also conceivable foronly a single computer system to be used that carries out the functionsmentioned under (b), (d), (e), (f) and (g).

1.-11. (canceled)
 12. A method for determining an amount required bycrop plants in a field of one or a plurality of plant protection agents,comprising the following steps: (A) detecting inhomogeneities in thefield, wherein the inhomogeneities indicate different existing and/orfuture growth stages of the crop plants in the field, (B) segmenting thefield into partial areas based on the inhomogeneities detected in step(A), (C) providing a plant growth model for the crop plants cultivatedin the field, (D) using the plant growth model on each partial area,wherein the temporal growth behavior of the crop plant is simulated foreach partial area, (E) determining a requirement of at least a portionof the crop plants cultivated in the field for treatment with one or aplurality of plant protection agents, and (F) calculating thepartial-area-specific required amount of one or a plurality of plantprotection agents based on the simulation of growth behavior in step (D)and the requirement determined in step (E).
 13. A method for treatingcrop plants in a field with one or a plurality of plant protectionagents, comprising the following steps: (A) detecting inhomogeneities inthe field, wherein the inhomogeneities indicate different existingand/or future growth stages of the crop plants in the field, (B)segmenting the field into partial areas based on the inhomogeneitiesdetected in step (A), (C) providing a plant growth model for the cropplants cultivated in the field, (D) using the plant growth model on eachpartial area, wherein the temporal growth behavior of the crop plant issimulated for each partial area, (E) determining a requirement of atleast a portion of the crop plants cultivated in the field for treatmentwith one or a plurality of plant protection agents, (F) calculating thepartial-area-specific required amount of one or a plurality of plantprotection agents based on the simulation of growth behavior of step (D)and based on the requirement determined in step (E), (G) preparing apartial-area-specific application map, wherein the application map is adigital representation of the field that indicates for individualpartial areas of the field the respective amount(s) of (the) plantprotection agent(s) to be applied, and (H) applying one or a pluralityof plant protection agents using the partial-area-specific applicationmap.
 14. The method as claimed in claim 12, wherein in step (A), remotesensing data on the field are analyzed, NDVI or LAI values forindividual partial areas of the field are calculated, and the NDVI orLAI values are referred to for calculating the partial-area-specificrequired amount of one or a plurality of plant protection agents in step(F).
 15. The method as claimed in claim 12, wherein a digital image ofthe field produced by means of remote sensors is used in step (A) arid apartial area is assigned to each pixel of the digital image.
 16. Themethod as claimed in claim 12, wherein a digital image of the fieldproduced by means of remote sensors is used in step (A) and adjacentpixels of the digital image that indicate the same value with respect toa growth parameter or no longer deviate from one another as a presetvalue are combined into a partial area.
 17. The method as claimed inclaim 12, characterized in that a prediction model is used fordetermining the requirement in step (E).
 18. The method as claimed inclaim 12, characterized in that the size of the partial areas is adaptedto the spray width of an application machine.
 19. The method as claimedin claim 12, characterized in that the plant protection agent is aherbicide, fungicide, or pesticide.
 20. A system comprising (a) adigital representation of a field in which crop plants are cultivated,wherein inhomogeneities are recorded in the digital representation,wherein the inhomogeneities provide information on different existingand/or future growth stages of the crop plants in the field, (b) meansfor segmenting the digital representation into partial areas based onthe inhomogeneities, (c) a plant growth model for the crop plantscultivated in the field, (d) means for using the plant model on eachpartial area, (e) means for receiving a requirement of at least aportion of the cultivated crop plants for treatment with one or aplurality of plant protection agents, (f) means for calculating therequired amount of one or a plurality of plant protection agents foreach partial area based on the simulations of the growth behavior, and(g) means for producing a partial-area-specific application map, whereinthe application map is a digital representation of the field thatindicates for individual partial areas of the field the respectiveamount(s) of (the) plant protection agent(s) to be applied.
 21. Thesystem as claimed in claim 20, wherein the digital representation of thefield is based on a satellite image and the inhomogeneities aredifferent vegetation indices or leaf area indices.
 22. A computerprogram product comprising a data carrier on which a computer program isstored, which can be loaded into the working memory of a computer andcauses the computer to carry out the following steps: (i) reading adigital representation of a field in which crop plants are cultivatedinto the working memory of the computer, wherein the field in thedigital representation is subdivided into partial areas, wherein atleast a portion of the partial areas differ with respect to existingand/or future growth behavior of the cultivated crop plants, (ii)calculating the growth behavior of the crop plants cultivated in thefield over time for each individual partial area by means of a plantgrowth model, (iii) receiving a requirement of at least a portion of thecultivated crop plants for treatment with one or a plurality of plantprotection agents, (iv) calculating the required amount of the one orplurality of plant protection agent(s) for each partial area based onthe calculated growth stage for the respective partial area of the cropplants cultivated there, and (v) outputting the plant protection agentrequirement for each partial area to a user.